There is a huge demand for wireless data transmission. In particular, an increasing number of users and devices are going to use wireless networks for data transmission. With an increasing number of data-intensive multimedia applications in addition to speech-oriented communications, for example, Internet access, video conferencing, and video streaming, the amount of data transmitted over wireless channels increases tremendously at a rapid pace.
The MIMO transmission technique based on the use of multiple transmit antennas and multiple receive antennas provides a number of advantages such as an increased spectrum efficiency and enhanced transmitter reliability to cater for huge data-transmission demands. In a MIMO wireless communication system, both the transmitter and the receiver are equipped with multiple antennas. For radio communication standards such as the IEEE 802.16 m standard, both Single User MIMO (SU-MIMO) and Multi-User MIMO (MU-MIMO) are supported in the downlink (DL) as well as the uplink (UL). In other words, in addition to SU-MIMO where only one user is scheduled in one Resource Unit (RU), standards such as the IEEE 802.16 m standard allow multiple users to be scheduled in one RU when MU-MIMO is employed.
For MU-MIMO, data sent to different users are multiplexed into the same RU, giving rise to co-channel interference. Scheduling is of utmost importance because scheduling can suppress the impact of fading and interference occurred in wireless channels. Furthermore, scheduling can increase bandwidth utilization, guarantee various QoS (Quality of Service) requirements, and improve system fairness so that data rates can be guaranteed for various services. This type of scheduling is also known as MIMO scheduling.
A radio communication standard such as the IEEE 802.16 m standard provides a complicated QoS architecture. Under such QoS architecture, there are mainly six types of services, namely:
(1) aGP (adaptive Granting and Polling service), e.g., E-gaming;
(2) BE (Best Effort service), e.g., E-mail;
(3) nrtPS (non-real-time Polling Service), e.g., FTP (File Transfer Protocol);
(4) rtPS (real-time Polling Service), e.g., VOD (Video on Demand), net meeting;
(5) UGS (Unsolicited Grant Service), e.g., VOIP (Voice over Internet Protocol); and
(6) ertPS (extended real-time Polling Service), e.g. VOIP with silence suppression.
These services are further classified into two categories: real-time applications and non-real-time applications. Non-real-time applications include nrtPS and BE, while real-time applications comprise rtPS, UGS, ertPS and aGP. For real-time applications, there are requirements on minimum data rates, maximum data rates, priority, and delay. For non-real-time applications, there are requirements on maximum data rates, minimum data rates, and priority, but delay is not a concern. In general, characteristics such as minimum data rates, maximum data rates, priority, and delay are known as QoS parameters.
Therefore, there is a need to maximize the system throughput and guarantee various QoS requirements by scheduling. However, some of the existing techniques focus on signaling processing but not on packet scheduling, for example, a technique disclosed in US20080248753A1. Some of the other existing techniques focus only on other objectives without maximizing the system throughput while guaranteeing QoS. For example, US20090034636A1 discloses a method for controlling feedback of preceding information in a MIMO communication system with an objective to reduce codebook feedback via a control mechanism.
There is also a need to satisfy up to four QoS parameters for the six above-mentioned services. However, some of the existing techniques focus on only a few of these QoS parameters or even none. For example, US20080037671A1 discloses a method and apparatus for wireless communications which selects a user based only on Channel Quality Information (CQI) and Channel State Information (CSI), but does not take into account the QoS parameters. Similar limitations are found in other techniques. M. Andrews, K. Kumaran, K. Ramanan, A. Stolyar, P. Whiting, “Providing Quality of Service over a Shared Wireless Link”, IEEE Communications Magazine, February, 2001, describe a modified largest weighted delay first (M-LWDF) scheduling algorithm and consider one QoS parameter only, i.e. delay, and the CQI. S. Shakkottai, T. S. Rappaport, P. C. Karlsson, “Cross-layer design for wireless networks”, IEEE Communications Magazine, December, 2003, describe an exponential queue length rule (EXP-Q) scheduling algorithm without considering any of the QoS parameters, instead focusing only on the traffic congestion and the channel capacity. This publication also describes an exponential waiting time rule (EXP-W) scheduling algorithm without considering any of the QoS parameters, only considering the waiting time of a packet in a queue and the channel capacity. T. E. Kolding, “QoS-Aware Proportional Fair Packet Scheduling with Required Activity Detection”, IEEE 64th Vehicular Technology Conference (VTC), 2006, describes a proportional fair with a barrier function scaling (PFB) scheduling algorithm whose key considerations are the minimum data rate and the proportional fair index, i.e. only one QoS parameter and the CQI. Similarly, US patent application US20090154419A1 also adopts the PFB scheduling algorithm and focuses on only one QoS parameter and the CQI. Furthermore, these existing techniques employ the same scheduling criterion for multiple spatial streams.
In particular, there is a need to provide scheduling in an MIMO-OFDM system. However, some of the existing techniques only focus on systems like a WCDMA system, for example, a technique disclosed in US20090103497A1.
Overall, there remains a need in the art for MIMO scheduling techniques which considers the QoS parameters such as delay, minimum data rate, maximum data rate, and priority, as well as CQI/CSI and traffic congestion, whilst satisfying the six service types as defined in the IEEE 802.16 m standard and providing different scheduling criteria for multiple spatial streams.